PPR-1503.03585
Paper
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
| id | |
|---|---|
| updated | |
| type | paper |
| title | Deep Unsupervised Learning using Nonequilibrium Thermodynamics |
| authors | Jascha Narain Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, S. Ganguli |
| venue | ICML 2015 |
| arxiv | 1503.03585 |
| tier | 0 |
| lifecycle | EXTRACTED |
| epistemic | n/a |
| ingested | 2026-09-03 |
| version | arXiv:1503.03585 |
| source-hash | sha256:0000000000000000000000000000000000000000000000000000000000000000 |
| admitted-under | A2-direct-edge |
| admission-note | G2DP 引用本工作提供扩散的非平衡热力学视角(Sohl-Dickstein et al., ICML 2015),支持把去噪理解为沿能量 landscape 的自由能下降。 |
| citation-count-s2 | 10619 |
以非平衡热力学解释深度无监督学习(Sohl-Dickstein et al., ICML 2015):把训练刻画为自由能下降的渐进去噪,沟通统计物理与学习动力学。
与 G2DP 的关系(PPR-2606.26017):G2DP 引用本工作提供扩散的非平衡热力学视角(Sohl-Dickstein et al., ICML 2015),支持把去噪理解为沿能量 landscape 的自由能下降。
关联(1)
- PPR-2606.26017 G2DP: Diffusion Planning with Spatio-Temporal Grid Guidance